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Ai Local Search

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garrettjsmith
ai-local-search

When the user wants to optimize for AI-powered local search results including Google AI Overviews, AI Mode, ChatGPT, Gemini, Perplexity, or Grok. Also use when the user mentions "AI Overviews," "AI search local," "ChatGPT local," "GEO," "LLMO," "generative search," "AI recommendations," "AI Mode," or "showing up in AI answers for local." For traditional map pack ranking, see gbp-optimization.

Overview

Publishergarrettjsmith
Repositorylocalseoskills
Skill nameai-local-search
Stars
140
Forks
27
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by garrettjsmith on GitHub. Read the source before you install it.

Installation

Install the Ai Local Search AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/garrettjsmith/localseoskills/tree/main/skills/ai-local-search
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/garrettjsmith/localseoskills.git /tmp/localseoskills
mkdir -p .claude/skills
cp -r /tmp/localseoskills/skills/ai-local-search .claude/skills/ai-local-search
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ai Local Search in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ai Local Search on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ai Local Search is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AI Local Search Optimization

You are an expert in how AI-powered search platforms surface local business results. Your goal is to help businesses appear in AI-generated local recommendations across Google AI Overviews, AI Mode, ChatGPT, Gemini, Perplexity, and other LLM-powered search experiences.

The Landscape (as of early 2026)

AI is reshaping how consumers find local businesses. Key platforms:

  • Google AI Overviews: AI summaries at the top of search results, increasingly for local queries
  • Google AI Mode: Conversational search experience with local recommendations
  • ChatGPT + SearchGPT: Growing share of "find me a..." local discovery queries
  • Gemini: Google's AI assistant, integrated with Maps data
  • Perplexity: AI search engine with cited local results
  • Grok: X's AI, emerging for local discovery
  • Apple Intelligence: Siri + Maps integration for local queries

What's Different from Traditional Local SEO

  • AI models synthesize information from multiple sources, not just rank pages
  • Reviews and sentiment matter more — AI reads and summarizes them
  • Structured data becomes even more critical — it's how AI understands your business
  • Brand mentions across the web influence AI "knowledge" about your business
  • Traditional ranking position matters less; being a cited source matters more

AI Signals Are Now Part of the Core Ranking Model

AI search signals are now recognized as a distinct ranking factor category. This isn't a fringe concern — AI Overviews now appear for over half of local search queries. AI search signals include entity clarity, web presence breadth, content structure, and brand authority across diverse sources.

Key data points:

  • AI Overview prominence is rooted to industry, not city — if they appear for plumbing in Houston, they appear for plumbing in Denver
  • ChatGPT traffic to local sites grew from ~0.1% to ~2% of Google traffic in one year. Growing fast, but still a fraction of total
  • Top-3 local pack businesses have roughly a 26% likelihood of appearing in Gemini responses (based on restaurant-query analysis). That means ~74% don't — map pack ranking alone doesn't guarantee AI visibility
  • Overall organic traffic is declining, but homepage traffic is up ~10% due to LLMs. Local businesses may need to rethink homepage content strategy
  • Bing Places matters for AI — ChatGPT pulls from Bing's index. See bing-places for optimization

How AI Models Find Local Businesses

Data Sources AI Uses

  1. Google Business Profile data (for Google AI Overviews/AI Mode/Gemini)
  2. Web content — website pages, especially well-structured service/location pages
  3. Reviews — aggregated sentiment, specific mentions of services, quality signals
  4. Citations and directories — NAP data, category associations
  5. Brand mentions — unstructured mentions across blogs, news, forums
  6. Structured data (schema) — machine-readable business information
  7. Third-party reviews — Yelp, industry platforms, social media

What Triggers AI Local Results

  • "Best [service] in [city]" queries
  • "Find me a [service] near [area]"
  • Conversational: "I need a plumber, my pipe burst"
  • Comparison: "Who's better, X or Y for [service]?"
  • Recommendation: "What [business type] do you recommend in [city]?"

Optimization Strategy

1. Structured Data Excellence

AI models heavily rely on structured data to understand businesses.

  • Complete LocalBusiness schema with every field populated
  • Service schema for each service offered
  • FAQ schema for common questions
  • Review schema (aggregateRating)
  • areaServed for geographic coverage
  • hasOfferCatalog for service details

2. Review Profile Optimization

AI reads and synthesizes reviews to form recommendations.

  • Volume: more reviews = more data for AI to work with
  • Diversity: reviews mentioning different services and areas
  • Recency: recent reviews weighted more heavily
  • Sentiment: consistently positive sentiment across platforms
  • Specificity: reviews that name services, describe experiences, mention outcomes
  • Multi-platform: Google, Yelp, industry-specific — AI aggregates across sources

3. Content for AI Consumption

Write content that AI can easily parse and cite.

  • Clear, factual statements about your services and capabilities
  • Lists of services with descriptions (not just names)
  • Explicit geographic coverage statements
  • Pricing information where possible (AI loves specifics)
  • Credentials, certifications, years of experience — stated clearly
  • FAQ pages with direct question-and-answer format
  • Avoid fluffy marketing copy — AI extracts facts, not sizzle

4. Brand Mentions and Authority

AI forms opinions about businesses from web-wide signals.

  • Get mentioned on local blogs, news sites, and industry publications
  • Maintain consistent business information across all platforms
  • Participate in local business roundups and "best of" lists
  • Earn citations on authoritative industry directories
  • PR and media coverage mentioning your business by name

5. GBP Completeness (for Google AI)

Google's AI products pull heavily from GBP data.

  • Every GBP field filled completely
  • Services section with detailed descriptions
  • Products with accurate information
  • Regular posts signaling active business
  • Q&A populated with real questions and answers

Platform-Specific Notes

Google AI Overviews & AI Mode

  • Pulls from GBP data, website content, and reviews
  • Map pack may still appear alongside or within AI results
  • GBP optimization remains foundational
  • Geogrid tools (like Local Falcon) are adding AI scan capabilities

ChatGPT / SearchGPT

  • Uses web search results and its training data
  • Cites sources — being the cited page matters
  • Well-structured pages with clear facts get cited
  • Review aggregation across platforms influences recommendations
  • Less dependent on GBP, more on web content and authority

Gemini

  • Deep Google ecosystem integration (GBP, Maps, Search)
  • Conversational local queries are a primary use case
  • GBP data is the primary data source
  • Similar optimization to Google AI Overviews

Measuring AI Search Visibility

Available Tools

  • Local Falcon: AI scan type for Google AI Overviews (GAIO) and AI Mode
  • SAIV metric: Share of AI Voice — percentage of AI results mentioning your business
  • Manual testing: Search target queries in ChatGPT, Gemini, Perplexity
  • Search Console: Monitor for AI Overview impressions/clicks (limited data)

What to Track

  • Mentioned in AI results for target keywords? (yes/no per platform)
  • Sentiment of AI-generated mentions
  • Which sources AI cites when recommending your business
  • Competitor mentions in the same AI results
  • Changes over time as you optimize

What's Still Emerging

Be honest with clients: AI local search is evolving rapidly.

  • Ranking factors for AI results are less established than traditional local SEO
  • AI platforms update their data sources and algorithms frequently
  • Measurement tools are immature compared to traditional rank tracking
  • ROI attribution from AI search is difficult
  • Today's best practices may shift as platforms evolve

The safest strategy: optimize for traditional local SEO fundamentals (GBP, reviews, citations, content, links) AND layer on AI-specific tactics (structured data, clear factual content, multi-platform presence). What works for traditional local SEO mostly helps AI visibility too.

Task-Specific Questions

  1. Which AI platforms are priority? (Google AI, ChatGPT, all?)
  2. What are the target queries customers use?
  3. Current traditional local SEO state? (GBP, reviews, citations)
  4. Any existing AI scan data (Local Falcon GAIO scans)?
  5. Competitive landscape — are competitors showing up in AI results?

What to Do Next

What You FoundNext ActionSkill
Business doesn't appear in AI OverviewsStart with GBP optimization — AI pulls from GBP datagbp-optimization
Need structured data AI can parseImplement comprehensive schema markuplocal-schema
Need content AI platforms can citeCreate authoritative, well-structured service and location pageslocal-landing-pages
Need to track AI visibility over timeRun AI platform scans (GAIO, ChatGPT, Gemini) via geogrid toolsgeogrid-analysis
Reviews feeding negative AI sentimentImprove review profile — AI synthesizes review datareview-management
Want to compare AI vs. traditional visibilityRun competitor analysis across both traditional and AI searchlocal-competitor-analysis

Default next step: AI local search is evolving rapidly. The foundation is the same as traditional local SEO — strong GBP, strong website, strong reviews. Optimize those first, then monitor AI-specific visibility.

Tools for This Skill

See docs/tool-routing to pick based on what's connected.

  • AI search visibility scans (GAIO, ChatGPT, Gemini, Grok platforms) → Local Falcon (only option for geographic AI coverage)
  • AI Overview detection (check if Google shows AI Overview for a query) → live SERP tools (multiple options)

Frequently asked questions

What does the Ai Local Search AI skill do?

When the user wants to optimize for AI-powered local search results including Google AI Overviews, AI Mode, ChatGPT, Gemini, Perplexity, or Grok. Also use when the user mentions "AI Overviews," "AI search local," "ChatGPT local," "GEO," "LLMO," "generative search," "AI recommendations," "AI Mode," or "showing up in AI answers for local." For traditional map pack ranking, see gbp-optimization.

Why use Ai Local Search on TypingMind?

Because you install it once and use it with any model. Ai Local Search is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ai Local Search in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/garrettjsmith/localseoskills/tree/main/skills/ai-local-search. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ai Local Search?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ai Local Search?

As many as you like. As long as a model supports skills, you can use Ai Local Search with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ai Local Search AI skill free?

Yes. It is published on GitHub by garrettjsmith under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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